POMDPs provide a rich framework for planning and control in partially observable domains. Recent new algorithms have greatly improved the scalability of POMDPs, to the point where...
Consider the task of a mobile robot autonomously navigating through an environment while detecting and mapping objects of interest using a noisy object detector. The robot must re...
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...
Sylvie C. W. Ong, Shao Wei Png, David Hsu, Wee Sun...
CRIKEY is a planner that separates out the scheduling from the classical parts of temporal planning. This can be seen as a relaxation of the temporal information during the classic...
The paper proposes a preventive maintenance (PM) planning model for the performance improvement of cellular manufacturing systems (CMS) in terms of machine reliability, and resour...